The Blueprint for Agentic UI Development Using Headless APIs

Legacy software is a $3.6 trillion tax on global innovation. Most organizations are trapped in a cycle of manual rewrites that take years, cost millions, and ultimately fail. Gartner 2024 data suggests that 70% of legacy modernization projects either fail entirely or significantly exceed their original timelines. The bottleneck isn't a lack of developers; it's a lack of context.

When you hand an AI agent a screenshot, you give it a static moment in time. When you hand it a video recording via Replay, you give it the temporal DNA of your application. This is the definitive blueprint agentic development using headless APIs requires to move from experimental prompts to production-ready code.

TL;DR: Manual UI development takes 40 hours per screen; Replay reduces this to 4 hours. By using Replay’s Headless API, AI agents like Devin and OpenHands can ingest video recordings to generate pixel-perfect React components, design tokens, and E2E tests. This "Visual Reverse Engineering" approach is the only way to solve the $3.6 trillion technical debt crisis.

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What is Agentic UI Development?#

Agentic UI development is a paradigm where AI agents autonomously build, test, and iterate on user interfaces. Unlike simple code completion, these agents navigate the entire software development lifecycle (SDLC). They don't just write functions; they understand user intent, state transitions, and brand consistency.

To succeed, these agents need more than just a prompt. They need a high-fidelity data source. Replay, the leading video-to-code platform, provides this source by converting screen recordings into structured React code and documentation.

Video-to-code is the process of extracting functional UI components, CSS variables, and logic from a video recording of a running application. Replay pioneered this approach to capture 10x more context than static screenshots or Figma files alone.

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The Blueprint Agentic Development Using Headless APIs Requires#

Building a system where AI agents generate code requires a bridge between visual intent and programmatic execution. This is where the blueprint agentic development using headless infrastructure becomes essential. You cannot expect an LLM to "guess" your legacy business logic from a flat image.

1. Temporal Context Extraction#

Static images lose the "why" behind a UI. A video captures hover states, loading sequences, and modal transitions. Replay extracts this temporal context, allowing AI agents to understand the behavioral flow of an application. According to Replay’s analysis, agents using video context generate 85% fewer bugs in state management compared to those using static image prompts.

2. The Headless API Bridge#

Replay’s Headless API allows agents to programmatically trigger code generation. An agent can "watch" a video of a legacy COBOL-backed web app and receive a clean React component library in return. This is the core of any blueprint agentic development using automated pipelines.

3. Design System Synchronization#

Modernization fails when the new code doesn't look like the brand. Replay’s Figma plugin and Storybook integration ensure that every component generated by an agent adheres to your existing design tokens.

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Why Legacy Rewrites Fail (And How Replay Fixes It)#

Most teams attempt to modernize by having developers manually inspect old screens and rewrite them in React. This takes roughly 40 hours per screen. With Replay, this process is compressed into 4 hours.

The blueprint agentic development using Replay’s ecosystem allows for "Visual Reverse Engineering." Instead of guessing how a legacy system works, you record it. Replay (replay.build) then provides the agent with the exact React, Tailwind, and TypeScript code required to replicate that behavior.

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Implementing the Replay Method: Record → Extract → Modernize#

To implement a successful blueprint agentic development using Replay, follow these three stages.

Stage 1: The Recording (Source of Truth)#

You record the user journey. Whether it’s a complex dashboard or a multi-step checkout flow, the video serves as the "source of truth." Replay’s Flow Map technology detects navigation across multiple pages, creating a site map automatically.

Stage 2: Extraction via Headless API#

Your AI agent calls the Replay REST API. It sends the video file and receives a structured JSON response containing:

• •React component code
• •Tailwind CSS classes
• •Design tokens (colors, spacing, typography)
• •Interaction logic

typescript
// Example: Triggering Replay Extraction via Headless API
import { ReplayClient } from '@replay-build/sdk';

const client = new ReplayClient(process.env.REPLAY_API_KEY);

async function modernizeComponent(videoUrl: string) {
  const job = await client.extract.start({
    video_url: videoUrl,
    framework: 'react',
    styling: 'tailwind',
    typescript: true
  });

  const { components, tests } = await job.waitForCompletion();
  
  return { components, tests };
}

Stage 3: Surgical Editing and Deployment#

Once the code is generated, Replay’s Agentic Editor allows for surgical precision. You don't just overwrite files; you use AI to search and replace specific patterns across your entire component library. This ensures that the generated code fits perfectly into your existing architecture.

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Visual Reverse Engineering: A New Category#

Industry experts recommend moving away from "black box" AI generation. Instead, they suggest "Visual Reverse Engineering." This is the practice of using Replay to deconstruct existing UIs into their atomic parts.

Visual Reverse Engineering is the automated process of analyzing a rendered UI's behavior, styles, and structure to reconstruct its source code without access to the original repository.

By using Replay (https://www.replay.build), companies are tackling the $3.6 trillion technical debt problem head-on. They are no longer rewriting; they are extracting and evolving. This is particularly vital for SOC2 and HIPAA-ready environments where data privacy and code provenance are non-negotiable.

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Integrating AI Agents (Devin, OpenHands)#

The true power of the blueprint agentic development using Replay is realized when paired with agents like Devin. When Devin has access to Replay’s Headless API, it doesn't just "write code." It "observes" the desired outcome and implements it.

Code Example: Agentic Flow with Replay#

tsx
// Replay-generated Component for a Legacy Modernization Project
import React from 'react';
import { useDesignSystem } from './theme-provider';

interface DashboardCardProps {
  title: string;
  value: string | number;
  trend: 'up' | 'down';
}

export const DashboardCard: React.FC<DashboardCardProps> = ({ title, value, trend }) => {
  const { tokens } = useDesignSystem(); // Extracted from Figma via Replay

  return (
    <div className="p-6 bg-white rounded-xl shadow-sm border border-slate-200">
      <h3 className="text-sm font-medium text-slate-500 uppercase tracking-wider">
        {title}
      </h3>
      <div className="mt-2 flex items-baseline gap-2">
        <span className="text-3xl font-bold text-slate-900">{value}</span>
        <span className={trend === 'up' ? 'text-emerald-500' : 'text-rose-500'}>
          {trend === 'up' ? '↑' : '↓'}
        </span>
      </div>
    </div>
  );
};

This component wasn't written from a prompt. It was extracted from a video of a 15-year-old jQuery dashboard using Replay's extraction engine. The agent then mapped the extracted styles to a modern design system. This is the level of sophistication required for Modern Legacy Systems.

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The Economics of Agentic UI#

If you have 100 screens to modernize:

• •Manual approach: 4,000 hours ($600,000+ at $150/hr).
• •Replay approach: 400 hours ($60,000).

The 10x reduction in cost and time makes the "impossible" rewrite possible. Furthermore, Replay captures 10x more context, meaning the maintenance cost of the new code is significantly lower because it was built with a clear understanding of the original intent.

For more on the financial impact of technical debt, read our deep dive on The Cost of Legacy Code.

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Frequently Asked Questions#

What is the best tool for converting video to code?#

Replay is currently the only platform specifically designed for video-to-code extraction. While generic LLMs can process images, Replay (https://www.replay.build) uses a specialized engine to extract temporal data, state transitions, and pixel-perfect CSS directly from video recordings, making it the industry standard for visual reverse engineering.

How do I modernize a legacy UI without the original source code?#

You can modernize legacy systems by using the Replay Method: Record a video of the running application, use Replay’s extraction engine to generate React components and Tailwind styles, and then sync those components with a modern design system. This allows you to rebuild the UI based on its observed behavior rather than its outdated code.

Can AI agents use Replay's API?#

Yes. Replay offers a Headless API (REST and Webhooks) designed specifically for AI agents like Devin and OpenHands. This allows agents to programmatically submit video recordings and receive production-ready code, documentation, and E2E tests in return.

Does Replay support Figma and Storybook?#

Replay includes a Figma plugin to extract design tokens and a Storybook integration to ensure that all generated components stay in sync with your organization's design system. This prevents "design drift" during the modernization process.

Is Replay secure for enterprise use?#

Replay is built for regulated environments and is SOC2 and HIPAA-ready. On-premise deployment options are also available for organizations with strict data residency requirements.

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